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Inducing Folksonomy GOAL: induce hidden classification hierarchies, “Folksonomies*,” from user generated metadata Although metadata from an individual user may be too inaccurate and incomplete, the metadata from different users may complement each other, making it, in combination, meaningful. In this work, we explore some strategies that combine metadata from many users and then induce folksonomies. * The definition is somewhat different from the original one, made by Thomas Vander Wal.

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Evaluation & Data Set Hypothesis: the approach that takes explicit relations into account can induce better hierarchies. “Better” means more consistent with the reference hierarchy (obtained from Open Directory Project (ODP)) ODP Hierarchy in ODP is created by volunteer editors controlled under ODP guidelines

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Metrics Taxonomic Overlap [adapted from Maedche02+] measuring structure similarity between two trees for each node, determining how many ancestor and descendant nodes overlap to those in the reference tree. Lexical Recall measuring how well an approach can discover concepts, existing in the reference hierarchy (coverage)

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Discussion Simple strategy to aggregate a large number of shallow relations specified by different users into a common, deeper hierarchy Induced hierarchies are more consistent with ODP Future work includes:  Term ambiguity  Global structure  Relation types  Apply to other datasets

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Questions? Is the metric used in evaluation meaningful? How is the scalability of the system? WordNet, ODP is already there. Why do we need this system? How is this work related to ontology enrichment? Is it ethical to collect users’ data? …. Questions? THANK YOU!